ampdepolymerase

For those who are interested, Petri nets have a lot of applications in CS, for example, spiking neural networks.

Isn't this the same technology as Focals by North?

Given enough time the industry would accumulate institutional knowledge that creates a massive moat. The knowledge and experience is siloed up. Better have boring academia where everyone benefits than to continue feeding corporate titans.

And that is basic research. It may be dry, boring, and tedious but somebody has to do the legwork. Throwing machine learning at it won't change things much either. Applied ML has a last mile problem - eventually you still need somebody to supervise the wet lab experiments/machines and all not so glorious bits that would never be featured in Nature or Science.

And luck too can be bought. With enough capital you can afford to play the game again and again.

The issue is that the structures to handle streaming are not often first class (in languages other than Go, Rust, and JavaScript). And when they are, the the third party interfaces are not. Eventually your data will have to reach the DB and it would bottleneck. Nobody wants to use KV storage all the time, SQL systems and ORMs need to step up their concurrency game.

Are SMT solvers insufficient?

The secret solution is called Z3.

A more precise but more expensive method would be to use phase array mics with license plate recognition cameras and just create a nominal fine.

Another issue is the obsession with regulating implementation, there really should not be any other terms to follow beyond power and general FCC interference guidelines. The stuff on encryption is obsolete and puts up unnecessary barriers in this day and age.

Are they not law enforcement?

This is like a modern day Access right?

The expensive bits are mainly the arms. Strictly speaking there is nothing stopping you from running it on one of those sub-hundred bots from AliExpress.